• 비파괴검사학회지
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• 제37권2호
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• pp.106-114
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• 2017

This paper presents an automated subsurface micro void detection technique based on pulsed infrared thermography for inspecting epoxy molding compounds (EMC) used in electronic device packaging. Subsurface micro voids are first detected and visualized by extracting a lock-in amplitude image from raw thermal images. Binary imaging follows to achieve better visualization of subsurface micro voids. A median filter is then applied for removing sparse noise components. The performance of the proposed technique is tested using 36 EMC samples, which have subsurface (below $150{\mu}m{\sim}300{\mu}m$ from the inspection surface) micro voids ($150{\mu}m{\sim}300{\mu}m$ in diameter). The experimental results show that the subsurface micro voids can be successfully detected without causing any damage to the EMC samples, making it suitable for automated online inspection.

• 전기학회논문지
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• 제60권1호
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• pp.174-183
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• 2011

This paper is about a bar code decoding algorithm developed for smart phone applications. The algorithm consists of bar code data extraction procedure, bar code signal estimation procedure, and bar code decoding procedure. To detect the peak bar code module, a DSTW had been applied because of its outstanding performance in ECG peak detection. In order to minimize errors due to non-uniform light effect, the proposed algorithm was acted as a baseline wandering filter based on module peaks detection. The algorithm had been tested to evaluate the performance under the conditions of blurring, non-uniformed light and white noises. The algorithm had shown excellent performance in reconstruction of bar code decoding, compared to other conventional methods. In order to show the possibility of applying the algorithm to a smart phone, a real UPC-A type 150 bar code pictures obtained from a smart phone camera was applied to the algorithm, achieving the correct recognition rate of 97.33%.

• Structural Engineering and Mechanics
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• 제41권5호
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• pp.663-673
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• 2012

A number of mode shape-based structure damage identification methods have been verified by numerical simulations or experiments for on-line structure health monitoring (SHM). However, many of them need a baseline mode shape generated by the healthy structure serving as a reference to identify damages. Otherwise these methods can hardly perform well when multiple cracks conditions occur. So it is important to solve the problems above. By aid of the fractal dimension method (FD), Qiao and Wang proposed a generalized fractal dimension (GFD) to detect the delamination damage. As a modification of GFD, Qiao and Cao proposed the approximate waveform capacity dimension (AWCD) technique to simplify the calculation of fractal and overcome the false peak appearing in the high mode shapes. Based on their valued work, this paper combined and applied the AWCD method and curvature mode shape data to detect multiple damages in beam. In the end, the identification properties of the AWCD for multiple damages have been verified by groups of Monte Carlo simulations and experiments.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2006년도 춘계종합학술대회
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• pp.796-799
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• 2006

본 논문은 스캔한 문서 및 전자 문서 등과 같은 문서 이미지에서의 기울기를 검출하는 기법을 제안하고 있다. 제안한 알고리즘은 처리 속도 향상을 위해 일정 비율로 축소된 이미지를 사용한다. 하지만 여전히 문서 전체를 대상으로 기울기를 검출하는 것은 많은 계산량을 요구하므로 대상영역(ROI)을 선택한다. 대상 영역은 모폴로지 연산을 통해 문자열을 하나의 긴 component로 연결하고 Labeling 과정을 통해 선택된다. 그리고 원본 이미지에서 문자의 baseline을 바탕으로 대상 영역에서 기울기를 검출한다. 실험결과를 통하여, 제안한 방법은 표나 그래프가 포함된 여러 종류의 문서 이미지에서 빠르고 정확한 기울기 값을 검출함을 확인할 수 있다.

• Structural Engineering and Mechanics
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• 제71권6호
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• pp.751-761
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• 2019

Lamb wave technology is a promising technology in the field of structural health monitoring and can be applied in the detection and monitoring of defects in plate structures. Based on the reconstruction algorithm for the probabilistic inspection of damage (RAPID), a Lamb-based detection and evaluation method of through-thickness rectangular notches in metal plates was proposed in this study. The influences of through-thickness rectangular notch length and the angle between sensing path and notch length direction on signals were further explored through simulations and experiments. Then a damage index calculation method which focuses on both phase and amplitude difference between detected signals and baseline signals was proposed. Based on the damage index difference between two vertically crossed sensing paths which pass through the notch in a sensor network, the notch direction identification method was proposed. In addition, the notch length was determined based on the damage index distribution along sensing paths. The experimental results showed that the image reconstructed with the proposed method could reflect the information for the evaluation of notches.

• Steel and Composite Structures
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• 제31권4호
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• pp.341-359
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• 2019

Non-monolithic concrete structural connections are commonly used both in new constructions and retrofitted structures where anchors are used for connections. Often, flaws are present in anchor system due to poor workmanship and deterioration; and methods available to check the quality of the composite system afterward are very limited. In case of presence of flaw, load transfer mechanism inside the anchor system is severely disturbed, and the load carrying capacity drops drastically. This raises the question of safety of the entire structural system. The present study proposes a wave propagation technique to assess the integrity of the anchor system. A chemical anchor (embedded in concrete) composite system comprising of three materials viz., steel (anchor), polymer (adhesive) and concrete (base) is considered for carrying out the wave propagation studies. Piezoelectric transducers (PZTs) affixed to the anchor head is used for actuation and the PZTs affixed to the surrounding concrete surface of the concrete-anchor system are used for sensing the propagated wave through the anchor interface to concrete. Experimentally validated finite element model is used to investigate three types of composite chemical anchor systems. Studies on the influence of geometry, material properties of the medium and their distribution, and the flaw types on the wave signals are carried out. Temporal energy of through time domain differentiation is found as a promising technique for identifying the flaws in the multi-layered composite system. The present study shows a unique procedure for monitoring of inaccessible but crucial locations of structures by using wave signals without baseline information.

• 대한임베디드공학회논문지
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• 제17권5호
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• pp.265-272
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• 2022

As the risk of lung cancer has increased, early-stage detection and treatment of cancers have received a lot of attention. Among various medical imaging approaches, computer tomography (CT) has been widely utilized to examine the size and growth rate of lung nodules. However, the process of manual examination is a time-consuming task, and it causes physical and mental fatigue for medical professionals. Recently, many computer-aided diagnostic methods have been proposed to reduce the workload of medical professionals. In recent studies, encoder-decoder architectures have shown reliable performances in medical image segmentation, and it is adopted to predict lesion candidates. However, localizing nodules in lung CT images is a challenging problem due to the extremely small sizes and unstructured shapes of nodules. To solve these problems, we utilize atrous spatial pyramid pooling (ASPP) to minimize the loss of information for a general U-Net baseline model to extract rich representations from various receptive fields. Moreover, we propose mixed-up attention mechanism of reverse, boundary and convolutional block attention module (CBAM) to improve the accuracy of segmentation small scale of various shapes. The performance of the proposed model is compared with several previous attention mechanisms on the LIDC-IDRI dataset, and experimental results demonstrate that reverse, boundary, and CBAM (RB-CBAM) are effective in the segmentation of small nodules.

• 대한임베디드공학회논문지
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• 제18권2호
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• pp.41-50
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• 2023

Gait analysis is an important tool in the clinical management of cerebral palsy, allowing for the assessment of condition severity, identification of potential gait abnormalities, planning and evaluation of interventions, and providing a baseline for future comparisons. However, traditional methods of gait analysis are costly and time-consuming, leading to a need for a more convenient and continuous method. This paper proposes a method for analyzing the posture of cerebral palsy patients using only smartphone videos and deep learning models, including a ResNet-based image tilt correction, AlphaPose for human pose estimation, and SmoothNet for temporal smoothing. The indicators employed in medical practice, such as the imbalance angles of shoulder and pelvis and the joint angles of spine-thighs, knees and ankles, were precisely examined. The proposed system surpassed pose estimation alone, reducing the mean absolute error for imbalance angles in frontal videos from 4.196° to 2.971° and for joint angles in sagittal videos from 5.889° to 5.442°.

• 천문학회지
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• 제56권1호
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• pp.35-40
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• 2023

We have been conducting a exoplanet search survey using Bohyunsan Observatory Echelle Spectrograph (BOES) for the last 18 years. We present the detection of exoplanet candidate in orbit around HD 18438 from high-precision radial velocity (RV) mesurements. The target was already reported in 2018 (Bang et al. 2018). They conclude that the RV variations with a period of 719 days are likely to be caused by the pulsations because the Lomb-Scargle periodogram of HIPPARCOS photometric and H_α EW variations for HD 18438 show peaks with periods close to that of RV variations and there were no correlations between bisectors and RV measurements. However, the data were not sufficient to reach a firm conclusion. We obtained more RV data for four years. The longer time baseline yields a more accurate determination with a revised period of 803 ± 5 days and the planetary origin of RV variations with a minimum planetary companion mass of 21 ± 1 M_Jup. Our current estimate of the stellar parameters for HD 18438 makes it currently the largest star with a planetary companion.

• 방송공학회논문지
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• 제23권6호
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• pp.855-865
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• 2018

음향 이벤트 인식은 다수의 음향 이벤트가 발생하는 환경에서 이를 인식하고 각각의 발생과 소멸 시점을 판단하는 기술로써 인간의 청각적 인지 특성을 모델화하는 연구다. 음향 장면 및 이벤트 인식 연구 그룹인 DCASE는 연구자들의 참여 유도와 더불어 음향 인식 연구의 활성화를 위해 챌린지를 진행하고 있다. 그러나 DCASE 챌린지에서 제공하는 데이터 세트는 이미지 인식 분야의 대표적인 데이터 세트인 이미지넷에 비해 상대적으로 작은 규모이며, 이 외에 공개된 음향 데이터 세트는 많지 않아 알고리즘 개발에 어려움이 있다. 본 연구에서는 음향 이벤트 인식 기술 개발을 위해 실내외에서 발생할 수 있는 이벤트를 정의하고 수집을 진행하였으며, 보다 큰 규모의 데이터 세트를 확보하였다. 또한, 인식 성능 개선을 위해 음향 이벤트 존재 여부를 판단하는 보조 신경망을 추가한 이중 CNN 구조의 알고리즘을 개발하였고, 2016년과 2017년의 DCASE 챌린지 기준 시스템과 성능 비교 실험을 진행하였다.